The present invention deals with the problem of intercellular interference, i.e. the decrease of transmission performance and quality due to the radio signal interference from radio traffic in adjacent cells in a cellular network.
The radio resources within a cell are usually limited, which means that a base station transceiver arrangement is not able to allocate a radio channel or radio link to every user of a mobile terminal which is active within the cell at every moment. Especially, modern mobile terminals are able to transmit and receive a lot of data information at high speeds, besides ordinary voice call communication. A lot of new services, e.g. Multi Media Services (MMS), are provided by the operators and other service providers. Said services demand user radio channels having enough bandwidth and transmission quality allowing data packet flows to be transmitted at high bit rates and received with a minimum of bit error rate and bit drop-out. Data services are expected to constitute a significant part of traffic in the third generation (3G) wireless networks. A number of technologies have been standardized to support high data rates and optimize the spectrum utilization of user downlink channels. High Data Rate (HDR) systems, defined in the 3GPP2 cdma 2000 IS-856 standard offer a maximum data rate of 2,4 Mbit/s over a signal bandwidth of 1,2 MHz, while their 3GPP equivalent High Speed Downlink Packet Access (HSDPA) systems offer a maximum data rate of around 10 Mbit/s over a signal bandwidth of 5 MHz. These systems deliver high spectral efficiency by using a TDMA-like strategy (the base station (BS) transmits at full power to only one user in each slot) with a combination of link adaptation, hybrid ARQ and opportunistic scheduling. Link adaptation refers to the adaptation of a user's transmission data rate to its radio conditions based on Data Rate control (DRC) signals sent back by the user to the base station. Hybrid ARQ (Automatic Repeat request) allows the transmission of any packet spread over multiple slots to be terminated early, i.e. as soon as the packet is successfully received, so as to adapt the transmission rate to the actual radio conditions. This control scheme, based on Chase combining or incremental redundancy, is essential given the errors in channel errors prediction and the necessarily conservative Signal-to-Noise Ratio (SINR) thresholds used to ensure a successful transmission
A scheduler may be defined as a radio resource allocation function that determines what radio resources (e.g. time and frequency domain channels, here also denoted chunks) are used by what users (or data flows) and at what time instants. Desired characteristics of a scheduler include low delay and high throughput.
Several different scheduling principles exist. Examples are First-In-First-Out, Round Robin, Max-Rate and Proportional Fair, as well as score-based schedulers. These have different characteristics in terms of required input, complexity, and achievable delay, throughput and fairness results.
The scheduling algorithm is a key component of these time-shared systems. In addition to exploiting multi-user diversity over short time-scales, this algorithm also determines how resources are shared over longer timescales. An algorithm that always selects the user with the highest data rate is efficient in term of overall throughput but may starve low SINR users, typically located far from the base station. An algorithm that equalizes the data rates of active users, on the other hand is fair but inefficient as most radio resources are used to sustain the data rate of distant users. A third strategy, which realizes a reasonable trade-off between efficiency and fairness, consists in transmitting to the user with the highest data rate relative to its current mean data rate. This scheduler, termed Proportional Fair (PF), is widely used in currently developed systems.
It is actually necessary to account for the fact that the actual set of active users is dynamic and varies as a random process as new data flows are initiated and others complete. As each data flow is characterized by some amount of data to be transferred, the resource attributed to any user determines how long that user will stay active. In particular, an “efficient” strategy that selects always near users results in a steady state where most users with data left in their buffers are far from the base station. A “fair” strategy, on the other hand, results in a much more favourable steady state where users are more uniformly distributed in the cell. The fair scheduling strategies are often the most efficient in terms of average performance.
The interference between cells depends on the radio traffic intensity and the, necessary transmitting power. The necessary transmitting power increases with the distance between a user terminal and the base station. The distribution of active users within a cell will therefore influence the transmission quality in neighbouring cells. As an example, a large number of active users, i.e. user terminals, close to the border of a cell will generate more interference on the radio traffic in neighbouring cells than the same number of active users close to the base station. Some schedulers are able to restrict the radio traffic from active “long-distance users” in favour for active “short-distance users”, while other schedulers work in favour for the active “long-distance users”. Schedulers are also able to control the quality of each user link, here denoted user quality, within the cell by adapting the transmission power according to one or a number of link quality criteria. Different schedulers may be used for various performance optimizations in a single-cell. However, in multi-cell networks it is of interest to maximize the performance (e.g. bit rates) across all cells, here denoted the network quality. This is not necessarily accomplished by locally maximizing data flow performance, i.e. data packet flow, in each cell, here denoted the intracellular quality. This is because the interference generated may cause more nuisance in neighbour cells than it does good in the own cell. For instance, if each scheduler within a block of cells reacts by increasing their transmission power to increase the user link quality, the interference between the cells will increase resulting in a decrease of user link quality.